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1.1 KiB
Meteos Architecture
Meteos is Machine Learning as a Service (MLaaS) in Apache Spark. Meteos create a workspace of Machine Learning via sahara spark plugin and manage some resources and jobs regarding Machine Learning.
Meteos components
Meteos consist of meteos-api service and meteos-engine service.
- meteos-api - web service which has REST interface.
- meteos-engine - service which manage Meteos resources.
Resources
Meteos manages these resources regarding machine learning.
- Experiment Template - Template which define experiment like number of master/worker nodes, spark version, base VM image, flavor, network, etc.
- Experiment - a workspace of Machine Learning.
- Data Set - a data parsed by user to create a Prediction Model.
- Prediction Model - a model produced by data mining and machine learning algorithms.
- Learning Job - a job which consists of input data, output data(predicted data), job status, job stdout/stderr.
The following diagram illustrates the architecture of mistral:
